Many existing software platforms are associated with multiple data-driven applications. All of these data-driven applications need to be monitored for timely problem identification and efficient troubleshooting. However, each of these applications may use different data sources and/or follow a different path for data processing, while all the applications are running on the same platform and sharing its resources.
Existing solutions for monitoring applications are restricted to monitoring at the cluster level, as opposed to individual applications. So, while a user could potentially detect issues with, for example, a data store, the user could not understand how those issues affect higher-level applications, nor could the user detect issues resulting from the higher-level application, etc.
There is thus a need for addressing these and/or other issues associated with the prior art.